The use of tacit knowledge has previously been shown to help expedite problem-solving procedures in the setting of medical emergency responses, as individuals can use past experiences in present and future challenges. However, there is a lack of understanding in its application in IT and socio-technical management. This paper examines the thought processes observed in Security Operational Centre (SOC) analysts facing threat events to lay the groundwork for tacit knowledge management in SOCs. Based on Sternberg's fieldwork in tacit knowledge, we conducted semi-structured interviews with ten analysts to explore the key artefacts and individual traits that aid their approach to communication, and to examine the thought processes under hypothetical incident handling scenarios. The results highlight a unanimous pursuit of Root Cause Analysis (RCA) upon the outbreak of an incident and stages of decision-making when escalating to third party support providers. Using Business Process Modelling and Notation (BPMN), we show the procedural elements of tacit knowledge from several scenarios. The results also suggest that simulation environments and physical proximity with analysts and vendors can facilitate the transfer of tacit knowledge more effectively in SOCs.

Sonification, in which data is represented as sound, can be used to turn network attacks and network-security information into audio signals. This could complement the range of security-monitoring tools currently used in Security Operations Centres (SOCs). Prior work in sonification for network monitoring has not assessed the effectiveness of the technique for enabling users to monitor network-security information. To this end, we aim to investigate the viability of using sonified network datasets to enable humans to detect (recognise the presence of some) and identify (understand the type of) network attacks. In this paper we report the results of a user study in which we assessed the utility of a network-traffic sonification system for representing network attacks. Our results show that by listening to the sonified network data, participants could detect attacks accurately and efficiently, including combinations of attacks, and identify the types of attacks. Musical experience had no significant effect on the ability of participants to use the sonification, and participants could detect attacks without training, yet improved performance through training. The results support the potential of sonification for use in network-security monitoring tasks. (C) 2019 Elsevier Ltd. All rights reserved.

High-fidelity rendering can be used to investigate Cultural Heritage (CH) sites in a scientifically rigorous manner. However, a high degree of realism in the reconstruction of a CH site can be misleading insofar as it can be seen to imply a high degree of certainty about the displayed scenewhich is frequently not the case, especially when investigating the past. So far, little effort has gone into adapting and formulating a Predictive Rendering pipeline for CH research applications. In this paper, we first discuss the goals and the workflow of CH reconstructions in general, as well as those of traditional Predictive Rendering. Based on this, we then propose a research framework for CH research, which we refer to as Cultural Heritage Predictive Rendering (CHPR). This is an extension to Predictive Rendering that introduces a temporal component and addresses uncertainty that is important for the scenes historical interpretation. To demonstrate these concepts, two example case studies are detailed.

Virtual reconstruction and representation of historical environments and objects have been of research interest for nearly two decades. Physically based and historically accurate illumination allows archaeologists and historians to authentically visualise a past environment to deduce new knowledge. This report reviews the current state of illuminating cultural heritage sites and objects using computer graphics for scientific, preservation and research purposes. We present the most noteworthy and up-to-date examples of reconstructions employing appropriate illumination models in object and image space, and in the visual perception domain. Finally, we also discuss the difficulties in rendering, documentation, validation and identify probable research challenges for the future. The report is aimed for researchers new to cultural heritage reconstruction who wish to learn about methods to illuminate the past.